autolens.AnalysisPoint

class AnalysisPoint

Bases: Analysis, AnalysisLensing

The analysis performed for model-fitting a point-source dataset, for example fitting the point-sources of a multiply imaged lensed quasar or supernovae of many source galaxies of a galaxy cluster.

The analysis brings together the data, model and non-linear search in the classes log_likelihood_function, which is called by every iteration of the non-linear search to compute a likelihood value which samples parameter space.

Parameters:

• point_dict (PointDict) – A dictionary containing the full point source dictionary that is used for model-fitting.

• solver (PointSolver) – The object which is used to determine the image-plane of source-plane positions of a model (via a Tracer).

• dataset – The imaging of the point-source dataset, which is not used for model-fitting but can be used for visualization.

• cosmology (LensingCosmology) – The cosmology of the ray-tracing calculation.

Methods

fit_from	rtype: FitPointDict
galaxies_via_instance_from	Create a list of galaxies from a model instance, which is used to fit the dataset.
log_likelihood_function	Determine the fit of the strong lens system of lens galaxies and source galaxies to the point source data.
log_likelihood_positions_overwrite_from	Call the positions overwrite log likelihood function, which add a penalty term to the likelihood if the positions of the multiple images of the lensed source do not trace close to one another in the source plane.
make_result
modify_after_fit	Overwrite this method to modify the attributes of the Analysis class before the non-linear search begins.
modify_before_fit	Overwrite this method to modify the attributes of the Analysis class before the non-linear search begins.
modify_model
output_profiling_info	Output the log likelihood function profiling information to hard-disk as a json file.
profile_log_likelihood_function	This function is optionally called throughout a model-fit to profile the log likelihood function.
save_attributes
save_latent_variables	Save latent variables that are computed during the analysis.
save_results
save_results_combined
should_visualize	Whether a visualize method should be called perform visualization, which depends on the following:
sky_via_instance_from	Create a sky from a model instance, which is used to fit the dataset.
tracer_via_instance_from	Create a Tracer from the galaxies contained in a model instance.
visualize
visualize_before_fit
visualize_before_fit_combined
visualize_combined
with_model	Associate an explicit model with this analysis.

Attributes

latent_variables

Custom quantities that are computed during the analysis.

log_likelihood_function(instance)

Determine the fit of the strong lens system of lens galaxies and source galaxies to the point source data.

Parameters:

instance – A model instance with attributes

Returns:

fit – A fractional value indicating how well this model fit and the model masked_dataset itself

Return type:

Fit